webAI Releases TwIL-8B Reasoning Model, Self-Tests Score 98.2 on MATH-500
webAI launches TwIL-8B, an 8.8B parameter reasoning model fine-tuned from IBM Granite, showing strong math and code performance but lagging in knowledge benchmarks.
webAI released TwIL-8B on November 4, 2026, a dense decoder-only reasoning model with 8.79 billion parameters. The model is post-trained from IBM's Granite 4.2 8B, aiming to deliver efficient capabilities in mathematics, code generation, and instruction following at a smaller scale.
According to the model card published by webAI, TwIL-8B achieves a score of 98.2 on the MATH-500 benchmark and 81.6 on LiveCodeBench (verbose variant). However, it performs relatively poorly on knowledge-intensive tasks: its GPQA Diamond score is 70.2, which is 11.5 points lower than Qwen3.5-9B, and its MMLU-Pro score is 76.5, also trailing behind the competitor.
The model comes in balanced and verbose variants, supporting a context window of 131,072 tokens. A quantized GGUF version is approximately 4.98 GiB, suitable for CPU or modest-VRAM GPU inference. Notably, all weights are released under a non-commercial license, and the performance metrics are self-reported by webAI without independent third-party verification.